CN114974452A - Method and device for determining control target of secondary conversion source - Google Patents
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Abstract
The application relates to the technical field of environmental science, in particular to a method and a device for determining a control target of a secondary transformation source, wherein the method comprises the following steps: obtaining a plurality of samples of first pollutants in the atmosphere, and determining the concentration of each pollution source corresponding to the first pollutants in the plurality of samples based on the plurality of samples and a positive definite matrix factorization (PMF) model; determining a first proportion of each pollutant in a second class of pollutants in a comprehensive source according to the concentration of each pollution source corresponding to the first class of pollutants in the plurality of samples, wherein the comprehensive source comprises a primary source and a secondary conversion source; determining a second proportion of each pollutant in the second class of pollutants in the primary source respectively based on the acquired emission list data; and determining a control target of a secondary conversion source based on the first proportion and the second proportion. By adopting the method and the device, the secondary transformation source can be managed and controlled.
Description
Technical Field
The application relates to the field of environmental science, in particular to a method and a device for determining a control target of a secondary conversion source.
Background
Along with the rapid development of economy and the acceleration of urbanization process in recent years, haze phenomenon which takes high-fine particles as main characteristics begins to appear in developing countries, wherein the dust of the particles with the particle size of 2.5 microns not only reduces atmospheric visibility, but also can enter human respiratory tracts and lungs to seriously damage human health. Thus now PM 2.5 Has become a public health concern worldwide. PM (particulate matter) 2.5 The components are complex and consist of organic and inorganic compounds, such as elements of earth crust, metal compounds, elemental carbon, inorganic ions and organic substances. At one time discharge except PM 2.5 Also accompanied by SO 2 、NO x And CO and other polluting gases. Wherein sulfur dioxide is mainly from the combustion of sulfur-containing fuels, such as the emission of industrial production processes of power plants, smelting of sulfur-containing ores, chemical industry, oil refining, sulfuric acid plants and the like, and residential heating and the like; NO x The system is respectively from a mobile source and a fixed source, wherein the mobile source is mainly discharged by tail gas of a motor vehicle, and the fixed source is mainly discharged by thermal power generation, industrial combustion and the like; CO is mainly derived from motor vehicle exhaust gases and incomplete emissions from coal combustion, so some gaseous pollutants can be used as indicators to identify the main emission sources.
The source analysis is to qualitatively identify the source of the pollutant and quantitatively calculate the sharing rate and contribution value of the atmospheric particulate emission source, and the main source analysis mainly comprises an emission source inventory method, a receptor model taking a pollution area as an object and a diffusion model taking a pollution source as an object. The method for the emission list comprises the steps of surveying and counting pollution sources through specific space and time scales, and establishing a pollution source list database according to activity levels and emission factor models of different sources, so that emission of different source types is evaluated, main pollution sources are determined, and the diffusion model predicts the space-time distribution of particulate matter concentration under different meteorological conditions based on the emission list. However, depending on meteorological data too much, the result may have a large uncertainty, the receptor model analyzes the contribution of different pollution sources to the receptor by inputting the Chemical Component concentration of the pollutant, and the common receptor models include CMB (Chemical Mass Balance), PCA (Principal Component Analysis), PMF (Positive Matrix Factorization), and the like.
At present, the PMF model is widely applied to analysis of environmental air quality data, is based on the assumption that aerosol types and distinguishable chemical characteristics and highly related compounds come from the same source, and needs to collect a receptor sample to analyze a particulate matter source and quantitatively obtain comprehensive source contribution of a primary source and a secondary conversion source, but the model has problems. The source-like contribution of specific contaminants, such as sulfides and nitrides, can only be quantified for secondary conversion sources, since it is generally believed that sulfides and nitrides are obtained from secondary conversion and not primary emission. However, only quantitative source-type comprehensive contributions, that is, the comprehensive contributions caused by primary emission and secondary conversion, can be given to other pollutants, because when the pollutants in the atmosphere can be obtained from the primary emission and the secondary conversion, the amount of the pollutants in the atmosphere, specifically, the amount of the pollutants in the atmosphere emitted from the primary emission and the amount of the pollutants in the atmosphere converted from the secondary conversion cannot be distinguished, that is, the contribution of the secondary conversion source cannot be determined, and thus the secondary conversion source cannot be controlled.
Disclosure of Invention
In order to solve the problem of the prior art, the embodiment of the application provides a method and a device for determining a control target of a secondary transformation source, which can control the secondary transformation source. The technical scheme is as follows:
according to an aspect of the present application, there is provided a method of determining a regulatory objective of a secondary conversion source, the method comprising:
obtaining a plurality of samples of first pollutants in the atmosphere, and determining the concentration of each pollution source corresponding to the first pollutants in the plurality of samples based on the plurality of samples and a positive definite matrix factorization (PMF) model;
determining a first proportion of each pollutant in a second class of pollutants in a comprehensive source according to the concentration of each pollution source corresponding to the first class of pollutants in the plurality of samples, wherein the comprehensive source comprises a primary source and a secondary conversion source;
determining a second proportion of each pollutant in the second class of pollutants in the primary source respectively based on the acquired emission list data;
and determining a control target of a secondary conversion source based on the first proportion and the second proportion.
Optionally, the first type of pollutant comprises PM 2.5 Components, ions, metals, and a labeling gas;
the second type of pollutant comprises PM 2.5 A component and a tag gas;
wherein the PM 2.5 The component comprising NO 3 - 、SO 4 2- 、NH 4 + 、Na + 、K + 、Mg 2+ 、Ca 2+ 、Cl-、Al、Si、K、Ca;
The ions comprising NO 3 - 、SO 4 2- 、NH 4 + 、Na + 、K + 、Mg 2+ 、Ca 2+ 、Cl - One or more of the above;
the metal comprises one or more of Al, Si, K, Ca, Mn, Fe, Cu, Zn, As, Ba and Pb;
the marker gas comprises NO 2 、SO 2 And one or more of CO.
Optionally, the determining a second proportion of each pollutant in the second type of pollutant in the primary source respectively based on the acquired emission inventory data includes:
acquiring emission list data, wherein the emission list data comprises the emission amount of each pollutant in the second type of pollutants corresponding to each pollution source;
and respectively determining a second proportion of each pollutant in the second type of pollutants in the primary sources according to the emission amount of each pollutant in the second type of pollutants corresponding to each pollution source.
Optionally, the determining, according to the emission amount of each pollutant corresponding to each pollution source in the second type of pollutant, a second proportion of each pollutant in the second type of pollutant in the primary source respectively includes:
determining the total emission of each pollutant in the second pollutants according to the emission of each pollutant in the second pollutants corresponding to each pollution source;
for each pollutant in the second type of pollutant, calculating a ratio of the emission to the total emission corresponding to said each pollutant source, and determining a second proportion in the primary sources.
Optionally, the determining a control target of a secondary conversion source based on the first proportion and the second proportion includes:
for each pollutant in the second type of pollutant, respectively determining the difference value of the first proportion and the second proportion of each pollution source;
and determining a control target of a secondary conversion source according to the difference.
Optionally, the determining a control target of the secondary conversion source according to the difference includes:
if the difference is larger than 0, comparing the difference with a first preset threshold, and if the difference is larger than or equal to the first preset threshold, determining the conversion of the pollution source corresponding to the difference to the pollutant corresponding to the difference as a control target of a secondary conversion source;
and if the difference is smaller than 0, comparing the difference with a second preset threshold, and if the difference is smaller than or equal to the second preset threshold, determining the emission of the pollutant corresponding to the difference from the pollutant corresponding to the pollution source corresponding to the difference as a control target of the primary conversion source.
Optionally, the determining a control target of a secondary conversion source based on the first proportion and the second proportion includes:
for each pollutant in the second type of pollutants, comparing the first proportion and the second proportion of each pollution source, and if the first proportion of a certain pollution source is greater than the second proportion, determining the conversion of the pollutant by the pollution source as a control target of a secondary conversion source; if the first proportion of a certain pollution source is smaller than the second proportion, the emission of the pollutant by the pollution source is determined as a control target of a primary source.
According to another aspect of the present application, there is provided an apparatus for determining a management target of a secondary conversion source, the apparatus including:
the system comprises an acquisition module, a detection module and a processing module, wherein the acquisition module is used for acquiring a plurality of samples of first pollutants in the atmosphere and determining the concentration of each pollution source corresponding to the first pollutants in the plurality of samples based on the plurality of samples and a positive definite matrix factorization (PMF) model;
the first determining module is used for determining a first proportion of each pollutant in the second type of pollutants in a comprehensive source according to the concentration of each pollution source corresponding to the first type of pollutants in the plurality of samples, wherein the comprehensive source comprises a primary source and a secondary conversion source;
the second determining module is used for determining a second proportion of each pollutant in the second type of pollutants in the primary source respectively based on the acquired emission list data;
and the third determination module is used for determining a control target of the secondary conversion source based on the first proportion and the second proportion.
Optionally, the first type of pollutant comprises PM 2.5 Components, ions, metals, and a labeling gas;
the second type of pollutant comprises PM 2.5 Composition and labelGas identification;
wherein the PM 2.5 The component comprising NO 3 - 、SO 4 2- 、NH 4 + 、Na + 、K + 、Mg 2+ 、Ca 2+ 、Cl-、Al、Si、K、Ca;
The ions comprising NO 3 - 、SO 4 2- 、NH 4 + 、Na + 、K + 、Mg 2+ 、Ca 2+ One or more of Cl < - >;
the metal comprises one or more of Al, Si, K, Ca, Mn, Fe, Cu, Zn, As, Ba and Pb;
the marker gas comprises NO 2 、SO 2 And one or more of CO.
Optionally, the second determining module is configured to:
acquiring emission list data, wherein the emission list data comprises the emission amount of each pollutant in the second type of pollutants corresponding to each pollution source;
and respectively determining a second proportion of each pollutant in the second type of pollutants in the primary sources according to the emission amount of each pollutant in the second type of pollutants corresponding to each pollution source.
Optionally, the second determining module is configured to:
determining the total emission of each pollutant in the second pollutants according to the emission of each pollutant in the second pollutants corresponding to each pollution source;
for each pollutant in the second type of pollutant, calculating a ratio of the emission to the total emission corresponding to said each pollutant source, and determining a second proportion in the primary sources.
Optionally, the third determining module is configured to:
for each pollutant in the second type of pollutant, respectively determining the difference value of the first proportion and the second proportion of each pollution source;
and determining a control target of a secondary conversion source according to the difference.
Optionally, the third determining module is configured to:
if the difference is larger than 0, comparing the difference with a first preset threshold, and if the difference is larger than or equal to the first preset threshold, determining the conversion of the pollution source corresponding to the difference to the pollutant corresponding to the difference as a control target of a secondary conversion source;
and if the difference is smaller than 0, comparing the difference with a second preset threshold, and if the difference is smaller than or equal to the second preset threshold, determining the emission of the pollutant corresponding to the difference from the pollutant corresponding to the pollution source corresponding to the difference as a control target of the primary conversion source.
Optionally, the third determining module is configured to:
for each pollutant in the second type of pollutants, comparing the first proportion and the second proportion of each pollution source, and if the first proportion of a certain pollution source is greater than the second proportion, determining the conversion of the pollutant by the pollution source as a control target of a secondary conversion source; if the first proportion of a certain pollution source is smaller than the second proportion, the emission of the pollutant by the pollution source is determined as a control target of a primary source.
According to another aspect of the present application, there is provided an electronic device including:
a processor; and
a memory for storing a program, wherein the program is stored in the memory,
wherein the program includes instructions that, when executed by the processor, cause the processor to perform the above-described method of determining a governing objective of a secondary conversion source.
According to another aspect of the present application, there is provided a non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the above method of determining a governing target of a secondary conversion source.
The application can obtain the following beneficial effects:
the method and the device can determine the control target of the secondary conversion source through the first proportion of the pollutants in the comprehensive source and the second proportion of the pollutants in the primary source. Therefore, the contribution of the secondary conversion source can be represented, the control target of the secondary conversion source can be determined for various pollutants, and the method is not limited to specific pollutants obtained by secondary conversion, so that auxiliary support is better provided for air quality management and air pollution prevention and control decisions.
Drawings
Further details, features and advantages of the present application are disclosed in the following description of exemplary embodiments, which is to be read in connection with the accompanying drawings, in which:
FIG. 1 illustrates a flow chart of a method of determining governing targets of secondary conversion sources according to an exemplary embodiment of the present application;
FIG. 2 shows a schematic block diagram of an apparatus for determining a regulation target of a secondary conversion source according to an exemplary embodiment of the present application;
FIG. 3 illustrates a block diagram of an exemplary electronic device that can be used to implement embodiments of the present application.
Detailed Description
Embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present application. It should be understood that the drawings and embodiments of the present application are for illustration purposes only and are not intended to limit the scope of the present application.
It should be understood that the various steps recited in the method embodiments of the present application may be performed in a different order, and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present application is not limited in this respect.
The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description. It should be noted that the terms "first", "second", and the like in the present application are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this application are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that reference to "one or more" unless the context clearly dictates otherwise.
The names of messages or information exchanged between a plurality of devices in the embodiments of the present application are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
The application provides a method for determining a control target of a secondary conversion source, which can be completed by a terminal, a server and/or other equipment with processing capacity. The method provided by the embodiment of the application can be completed by any one of the devices or can be completed by a plurality of devices together.
The method will be described with reference to a flowchart of a method for determining a management and control target of a secondary conversion source shown in fig. 1.
Step 101, obtaining a plurality of samples of the first type of pollutants in the atmosphere, and determining the concentration of each pollution source corresponding to the first type of pollutants in the plurality of samples based on the plurality of samples and a positive definite matrix factorization (PMF) model.
Optionally, the first type of pollutant may include PM 2.5 Components, ions, metals, and a labeling gas. Wherein PM 2.5 The component comprising NO 3 - 、SO 4 2- 、NH 4 + 、Na + 、K + 、Mg 2+ 、Ca 2+ 、Cl - Al, Si, K, Ca; the ions comprising NO 3 - 、SO 4 2- 、NH 4 + 、Na + 、K + 、Mg 2+ 、Ca 2+ 、Cl - One or more of the above; the metal comprises one or more of Al, Si, K, Ca, Mn, Fe, Cu, Zn, As, Ba and Pb; the marker gas comprising NO 2 、SO 2 And one or more of CO. The present embodiment is not limited to specific contaminants.
In a possible embodiment, a plurality of samples of the atmosphere about the first type of pollutant can be obtained by the monitoring station, the plurality of samples can be concentration samples of the first type of pollutant in the atmosphere at the same position and collected at different times, the plurality of samples can form a binary matrix, as exemplified in table 1 below, data from a second row in table 1 goes down, each row represents data of one sample, certain data represents the concentration of certain pollutant in certain sample, and the unit of each data is μ g/m 3 . For example, the data in row 2, column 1 is 70.1, indicating PM in the first sample 2.5 Has a concentration of 70.1. mu.g/m 3 。
TABLE 1
The PMF model is widely applied to analysis of environmental air quality data, and the basic principle is as follows:
a particular data set can be viewed as a data matrix X of dimension n X m, where n samples and m chemicals are measured, i.e. a matrix of particular sample data is decomposed into two matrices: factor contribution and factor profile. The rows and columns of X and the correlation matrix are indexed by i and j, respectively, such that the goal of PMF modeling is to determine the number of factors p, the species profile f for each factor k k And the mass g contributed by each factor k to each individual sample k The amount of (a) is as follows (1):
wherein e is ij Is the residual error, g k Columns G, f representing factor contribution matrices k Number of rows, c, of the factor profile matrix f ij The modeled fraction for each sample/species.
Among PMFs, the analysis considered most useful is Q (Robust) And Q (true) A value of (a), and Q or Q/Q expected How to vary in different situations, e.g. different number of factors or different species inclusion/exclusion. If the uncertainty of the input data has been fine-tuned, resulting in a meaningful proportional residual, then the discussion of the Q value is not meaningful, but rather varying the Q value under different circumstances is very helpful in choosing different solutions (e.g., different factor numbers). It may be stated that the factor for a selection may be too high when Q becomes less varying as the factor increases. Q also affects the error analysis of the model, so Q is calculated expected If the selected Q value of the model is significantly different from the expected value, the DISP error analysis is not valid. The solution to the PMF minimizes the objective function Q based on the estimated data uncertainty, as follows (2):
uncertainty analysis in the PMF model presents a range of reliable estimates for each element of the matrix F, which may contain the true value of F. The main uncertainty in PMF comes from the rotational ambiguity in the model, so the same Q value would correspond to multiple solutions (G, F). There are three main reasons for the uncertainty of the PMF model: (1) random errors in the data values, i.e. errors generated during the measurement process; (2) rotating the ambiguity; (3) model error.
The method utilizes Bootstrap (BS) and Displacement (DISP) errors of a section, adds new variables (polluted gas) into an input file, evaluates main sources of the new variables, quantifies contribution values of particles and gaseous pollutants in ambient air, and quantifies the contribution values of the added polluted gas to the particles in the environment, wherein the method comprises the following steps: using PM 2.5 And chemical components and pollution gas thereof as indicators for one timeThe direct contribution of the emissions source and the secondary emissions source is quantified. By adding the gas indicator into the model, the contributions caused by primary emission, secondary emission sources and conversion are analyzed, so that the accuracy of factor spectrogram identification is improved.
The application inputs data including: species concentration and uncertainty, species concentration, missing values, concentration below detection limit and uncertainty were pre-processed according to the EPA PMF 5.0 instruction manual, where uncertainty is calculated as follows (3):
wherein, c ij Is the concentration of the jth variable in the ith sample; MDL is the detection limit. The contaminated gas data are from 23 hour averages. The species is judged according to the value of the signal-to-noise ratio (S/N): strong, weak, and bad, where weak is three times the uncertainty provided, and bad excludes the species. For uncertainty analysis, the number of BS runs is 100 and each factor is required to map over 80% of the BS runs.
It should be noted that the PFM algorithm adopted in the present application is a PFM algorithm commonly used in the prior art, and therefore, detailed operation processes and principles of the PFM algorithm are not described in detail.
Based on the multiple samples and the PMF model, the concentration of the first type of pollutant in the multiple samples corresponding to each pollution source can be obtained, and the concentration can be described by using a binary matrix. The following Table 2 illustrates the values in Table 2, which represent the concentration of a contaminant of the first type corresponding to factor 1 in μ g/m 3 。
TABLE 2
The output result shows that 5 factors are obtained by final analysis, and the factors are respectively: (1) raising a dust source; (2) a coal-fired source; (3) a vehicle source; (4) an industrial source; (5) a biomass combustion source. Because the same source has similar source composition spectrum characteristics in all the analysis results, main species and characteristic species emitted by different pollution sources are combined according to different species concentrations and contribution ratios in various factors, so as to distinguish the pollution source represented by each factor in the analysis results, and the detailed explanation and analysis of various factors are as follows:
(1) in the factor 1, the dust sources include road dust and building dust, wherein the ratio of Ca, Si, Mg, Fe and the like is high, and the dust sources are mainly primary sources by default in the embodiment of the application.
(2) Of the factor 2, the species contributing more is Cl - And Na + Usually mainly from the combustion process, the presence of higher NO in this factor 2 、SO 2 CO, these are also the major combustion products, and this factor is therefore defined as the source of combustion.
(3) In the factor 3, Al, Mn, Fe, Cu, Zn and Ba have higher proportion in the factor 3, and the factor has higher proportion to NO 2 CO contribution is high, so this factor is defined as automotive source.
(4) In factor 4, Na + 、Mg 2+ 、Ca 2+ Higher in factor 4, less polluting gas, and therefore defined as an industrial source.
(5) Factor 5, K + 、SO 4 2- The ratio of characteristic species is high, and CO and SO are simultaneously generated 2 There is also a higher contribution and is therefore defined as a source of biomass combustion.
Step 102, determining a first proportion of each pollutant in the second class of pollutants in the comprehensive source according to the concentration of each pollution source corresponding to the first class of pollutants in the plurality of samples.
Wherein, the comprehensive sources comprise a primary source and a secondary conversion source. Optionally, the second type of pollutant comprises PM 2.5 A component and a tag gas; PM (particulate matter) 2.5 The component comprising NO 3 - 、SO 4 2- 、NH 4 + 、Na + 、K + 、Mg 2+ 、Ca 2+ 、Cl - Al, Si, K, Ca; the marker gas comprising NO 2 、SO 2 And one or more of CO.
In one possible embodiment, after determining the concentration of the first type of pollutant in the plurality of samples corresponding to each pollution source, a normalization method may be used to quantify PM in the plurality of samples 2.5 And identifying the proportion of gas in each of the integrated sources.
Specifically, the step 102 may include the following steps 1021-.
Step 1021, calculating PM in a plurality of samples 2.5 Or the total concentration of the marker gas corresponding to the integrated source.
In one possible embodiment, the PM may be mixed with a mixture of water and air 2.5 Or the concentration of each pollution source corresponding to the identification gas is added to obtain the total concentration of the corresponding comprehensive source of the pollutant.
For example, assume PM among the plurality of samples obtained in step 101 above 2.5 And the concentration of each pollution source for the marker gas is shown in Table 3 below, the PM is calculated 2.5 The total concentration corresponding to the combined source is 13.01+14.53+4.10+13.94 is 45.58.
TABLE 3
Coal-fired source | Motor vehicle source | Industrial source | Biomass combustion source | |
PM2.5 | 13.01 | 14.53 | 4.10 | 13.94 |
SO2 | 28.03 | 7.05 | 5.66 | 20.56 |
NO2 | 21.39 | 21.51 | 8.40 | 16.14 |
CO | 16.75 | 17.79 | 3.17 | 19.77 |
Step 1022, calculate PM 2.5 Or identifying a ratio of the concentration of each pollutant in the gas corresponding to each source of pollution to the total concentration of the pollutant corresponding to the combined source.
In one possible embodiment, PM is calculated, again taking the example of Table 3 above 2.5 The ratio in the combined source is 13.01 ÷ 45.58 ÷ 28.5%. By analogy, the respective proportions of each contaminant in the combined source can be obtained, as shown in table 4 below.
TABLE 4
Coal-fired source | Motor vehicle source | Industrial source | Biomass combustion source | |
PM 2.5 | 28.5% | 31.9% | 9.0% | 30.6% |
SO 2 | 45.7% | 11.5% | 9.2% | 33.5% |
NO 2 | 31.7% | 31.9% | 12.5% | 23.9% |
CO | 29.1% | 31.0% | 5.5% | 34.4% |
And 103, determining a second proportion of each pollutant in the second type of pollutants in the primary sources respectively based on the acquired emission list data.
Wherein the emission inventory data may include an amount of each pollutant in the second class of pollutants for each pollution source. It is generally considered that the discharge amount recorded by the discharge list refers to the discharge amount of pollutants generated by one discharge, and the corresponding pollution source can be called as a primary source.
Optionally, the processing of step 103 may be as follows: acquiring emission list data; and respectively determining the second proportion of each pollutant in the second type of pollutants in the primary sources according to the emission amount of each pollutant in the second type of pollutants corresponding to each pollution source.
In a possible embodiment, since a plurality of pollution sources are determined in step 102, the emission amount corresponding to the second type of pollutant can be obtained from the relevant data of the plurality of pollution sources in the emission list.
Table 5 below illustrates an example, where the data in table 5 represents the emissions of the pollutant source corresponding to the emission of pollutants, and the unit of the data is ton.
TABLE 5
Combustion source | Motor vehicle source | Industrial source | Biomass combustion source | |
PM 2.5 | 199 | 671 | 2269 | 545 |
SO 2 | 724 | 377 | 587 | 89 |
NO 2 | 2635 | 14153 | 637 | 263 |
CO | 10599 | 14351 | 46878 | 4993 |
Further, the proportion of the pollutant emitted by each pollution source can be determined. Specifically, the following processing may be performed: determining the total emission of each pollutant in the second pollutants according to the emission of each pollutant in the second pollutants corresponding to each pollution source; for each pollutant in the second class of pollutants, a ratio of emissions to total emissions for each pollution source is calculated and determined as a second percentage in the primary source.
Taking Table 5 above as an example, SO is calculated 2 Total emission of 724+377+587+89 equals 1777 tons of SO 2 The proportion of the corresponding combustion source is 724 ÷ 1777 ═ 40.7%, and so on, every pollutant in the second class of pollutants can be obtainedEach contaminant corresponds to the proportion of each source of contamination, as shown in table 6 below.
TABLE 6
Combustion source | Motor vehicle source | Industrial source | Biomass combustion source | |
PM 2.5 | 5.4% | 18.2% | 61.6% | 14.8% |
SO 2 | 40.7% | 21.2% | 33.0% | 5.0% |
NO 2 | 14.9% | 80.0% | 3.6% | 1.5% |
CO | 13.8% | 18.7% | 61.0% | 6.5% |
And 104, determining a control target of the secondary conversion source based on the first proportion and the second proportion.
There are many methods for determining the control target of the secondary transformation source, and the application lists the following two possible methods:
the first method comprises the following steps: for each pollutant in the second type of pollutant, respectively determining the difference value of the first proportion and the second proportion of each pollution source; and determining a control target of the secondary transformation source according to the difference.
Specifically, for each pollutant in the second type of pollutant, a difference value between a first proportion and a second proportion of each pollution source is respectively determined; if the difference is larger than 0, comparing the difference with a first preset threshold, and if the difference is larger than or equal to the first preset threshold, determining the corresponding pollution source as a control target of a secondary conversion source; and if the difference is smaller than 0, comparing the difference with a second preset threshold, and if the difference is smaller than or equal to the second preset threshold, determining the corresponding pollution source as a control target of the primary conversion source.
The first preset threshold and the second preset threshold may be set according to the requirement of the user, which is not limited in the embodiments of the present invention.
Taking the above tables 4 and 6 as examples, the corresponding values in tables 4 and 6 are subtracted, that is, the corresponding values in table 6 are subtracted from the values in table 4 to obtain the difference, as shown in table 7 below.
TABLE 7
Coal-fired source | Motor vehicle source | Industrial source | Biomass combustion source | |
PM 2.5 | 23.1% | 13.7% | -52.6% | 15.8% |
SO 2 | 5.0% | -9.7% | -23.7% | 28.5% |
NO 2 | 16.8% | -48.1% | 8.9% | 22.4% |
CO | 15.3% | 12.3% | -55.5% | 27.9% |
In table 7, if a certain value is a positive number (i.e., the difference is greater than 0), it indicates that the contribution of the pollution source in the atmosphere to the pollutant is increased after the pollutant corresponding to the value is emitted by the pollution source corresponding to the value, and further indicates that the pollution source performs secondary conversion on the pollutant. The value can represent the degree of the secondary conversion source, that is, the larger the value is, the larger the degree of the secondary conversion of the pollutant to the pollutant is, and thus in principle, the control target of the secondary source can be determined by the difference. And comparing the value with a first preset threshold, and if the value is greater than the first preset threshold, indicating that the degree of secondary conversion of the pollutant to the pollutant source is great, so that the pollution source corresponding to the value can be determined as a control target of the secondary conversion source.
If a certain numerical value is a positive number, but the numerical value is smaller than the first preset threshold, it is indicated that although the pollutant corresponding to the numerical value is subjected to secondary conversion on the pollutant corresponding to the numerical value, the degree of the secondary conversion is very small and can be almost ignored, and therefore, the pollutant corresponding to the numerical value cannot be determined as the control target of the secondary conversion source in this case.
If a certain value is equal to 0, it indicates that the pollution source corresponding to the value has no change or a small change in the atmosphere after the pollutant corresponding to the value is discharged, and further indicates that the pollution source corresponding to the value has no secondary conversion or has a small secondary conversion on the pollutant corresponding to the value, and therefore, the pollution source corresponding to the value does not need to be determined as a control target of the secondary conversion source.
If a certain numerical value is less than 0, the concentration of the pollutant in the atmosphere is reduced after the pollutant corresponding to the numerical value is discharged by the pollution source corresponding to the numerical value, and the concentration of the pollutant when the pollutant is discharged by the pollution source is larger. And comparing the value with a second preset threshold, and if the value is less than or equal to the second preset threshold, indicating that the concentration of the pollutant source at the time of initially discharging the pollutant is very high, so that the pollutant source corresponding to the value is determined as the control target of the first source.
If a value is smaller than 0 but greater than the second preset threshold, it indicates that the difference between the concentration of the pollutant source corresponding to the value when the pollutant is initially emitted and the concentration of the pollutant source corresponding to the pollutant in the atmosphere is not large, and in this case, the pollutant source corresponding to the value may not be determined as the control target of the primary source.
Taking the above table 7 as an example, in table 7, assuming that the first preset threshold is 10% and the second preset threshold is-10%, the difference corresponding to the coal-fired source and the difference corresponding to the biomass combustion source are positive numbers and greater than 10%, and the vehicle source is for PM 2.5 And the difference corresponding to CO is positive and greater than 10%, for NO from industrial sources 2 Corresponding difference is positive and greater than 10%, for PM 2.5 CO and SO 2 The corresponding difference values are all negative numbers and less than 10%, and the vehicle source is NO 2 If the corresponding difference is negative and less than 10%, the following control objectives can be obtained:
supplying a coal-fired source and a biomass-fired source to the PM 2.5 Determining the secondary conversion of each polluted gas as a control target; source pair PM of motor vehicle 2.5 Determining the secondary conversion of CO as a control target; using industrial source to NO 2 Determining the secondary conversion as a control target;
industrial source to PM 2.5 CO and SO 2 Is determined as a control target for the primary source, and the motor vehicle source is used to control NO 2 Is determined as a regulatory target for the primary source.
And the second method comprises the following steps: for each pollutant in the second type of pollutants, comparing the first proportion and the second proportion of each pollution source, and if the first proportion of a certain pollution source is greater than the second proportion, determining the conversion of the pollution source to the pollutant as a control target of a secondary conversion source; if the first proportion of a certain pollution source is smaller than the second proportion, the emission of the pollution source to the pollutant is determined as a control target of a primary source.
If the first proportion of a certain pollution source is larger than the second proportion, the contribution of the pollution source to the pollutant in the atmosphere is increased after the corresponding pollutant is emitted by the pollution source, and further the pollution source carries out secondary conversion on the pollutant, so that the conversion of the pollution source to the pollutant is determined as a control target of the secondary conversion source.
If the first proportion of a certain pollution source is smaller than the second proportion, the concentration of the pollution source in the atmosphere corresponding to the pollutant is reduced after the pollution source discharges the corresponding pollutant, the concentration of the pollution source in the atmosphere corresponding to the pollutant is further explained to be larger than the concentration of the pollution source in the atmosphere corresponding to the pollutant when the pollution source initially discharges the pollutant, and the concentration of the pollutant initially discharged by the pollution source is further explained to be higher, so that the discharge of the pollution source to the pollutant is determined as a control target of a primary source.
If the first proportion of a certain pollution source is equal to the second proportion, the pollution source corresponding to the value has no change or little change in the atmosphere after discharging the pollutant corresponding to the value, and further the pollution source corresponding to the value has no secondary conversion or little secondary conversion on the pollutant corresponding to the value, so that the pollution source corresponding to the value does not need to be determined as a control target of the secondary conversion source.
The embodiment of the application can obtain the following beneficial effects:
in the embodiment of the application, the control target of the secondary conversion source can be determined through the first proportion of the pollutants in the comprehensive source and the second proportion of the pollutants in the primary source. Therefore, the contribution of the secondary conversion source can be represented, the control target of the secondary conversion source can be determined for various pollutants, and the method is not limited to specific pollutants obtained by secondary conversion, so that auxiliary support is better provided for air quality management and air pollution prevention and control decisions.
The embodiment of the application provides a device for determining a control target of a secondary conversion source, and the device is used for realizing the evaluation method for determining the control target of the secondary conversion source. As shown in fig. 2, the apparatus 200 for determining the management target of the secondary conversion source includes: the device comprises an acquisition module 201, a first determination module 202, a second determination module 203 and a third determination module 204.
An obtaining module 201, configured to obtain multiple samples of a first type of pollutant in the atmosphere, and determine, based on the multiple samples and a positive definite matrix factorization PMF model, a concentration of each pollution source corresponding to the first type of pollutant in the multiple samples;
a first determining module 202, configured to determine, according to a concentration of each pollution source corresponding to a first type of pollutant in the plurality of samples, a first proportion of each pollutant in a second type of pollutant in a comprehensive source, where the comprehensive source includes a primary source and a secondary conversion source;
the second determining module 203 is configured to determine, based on the obtained emission list data, a second proportion of each pollutant in the second class of pollutants in the primary source;
a third determining module 204, configured to determine a management and control target of the secondary conversion source based on the first percentage and the second percentage.
Optionally, the first type of pollutant comprises PM 2.5 Components, ions, metals, and a labeling gas;
the second type of pollutants comprises PM 2.5 A component and a tag gas;
wherein the PM 2.5 The component comprising NO 3 - 、SO 4 2- 、NH 4 + 、Na + 、K + 、Mg 2+ 、Ca 2+ 、Cl - 、Al、Si、K、Ca;
The ions comprising NO 3 - 、SO 4 2- 、NH 4 + 、Na + 、K + 、Mg 2+ 、Ca 2+ 、Cl - One or more of the above;
the metal comprises one or more of Al, Si, K, Ca, Mn, Fe, Cu, Zn, As, Ba and Pb;
the marker gas comprises NO 2 、SO 2 And one or more of CO.
Optionally, the second determining module 203 is configured to:
acquiring emission list data, wherein the emission list data comprises the emission amount of each pollutant in the second type of pollutants corresponding to each pollution source;
and respectively determining a second proportion of each pollutant in the second pollutants in the primary sources according to the emission amount of each pollutant in the second pollutants corresponding to each pollution source.
Optionally, the second determining module 203 is configured to:
determining the total emission of each pollutant in the second pollutants according to the emission of each pollutant in the second pollutants corresponding to each pollution source;
for each pollutant in the second type of pollutant, calculating a ratio of the emission to the total emission corresponding to said each pollutant source, and determining a second proportion in the primary sources.
Optionally, the third determining module 204 is configured to:
for each pollutant in the second type of pollutant, respectively determining the difference value of the first proportion and the second proportion of each pollution source;
and determining a control target of a secondary conversion source according to the difference.
Optionally, the third determining module 204 is configured to:
if the difference is larger than 0, comparing the difference with a first preset threshold, and if the difference is larger than or equal to the first preset threshold, determining the conversion of the pollution source corresponding to the difference to the pollutant corresponding to the difference as a control target of a secondary conversion source;
and if the difference is smaller than 0, comparing the difference with a second preset threshold, and if the difference is smaller than or equal to the second preset threshold, determining the emission of the pollutant corresponding to the difference from the pollution source corresponding to the difference to the pollutant corresponding to the difference as a control target of the primary conversion source.
Optionally, the third determining module 204 is configured to:
for each pollutant in the second type of pollutants, comparing the first proportion and the second proportion of each pollution source, and if the first proportion of a certain pollution source is greater than the second proportion, determining the conversion of the pollutant by the pollution source as a control target of a secondary conversion source; if the first proportion of a certain pollution source is smaller than the second proportion, the emission of the pollutant by the pollution source is determined as a control target of a primary source.
In the embodiment of the application, the control target of the secondary conversion source can be determined through the first proportion of the pollutants in the comprehensive source and the second proportion of the pollutants in the primary source. Therefore, the contribution of the secondary conversion source can be represented, the control target of the secondary conversion source can be determined for various pollutants, and the method is not limited to specific pollutants obtained by secondary conversion, so that auxiliary support is better provided for air quality management and air pollution prevention and control decisions.
An exemplary embodiment of the present application also provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor. The memory stores a computer program executable by the at least one processor, the computer program, when executed by the at least one processor, is for causing the electronic device to perform a method according to an embodiment of the application.
The exemplary embodiments of this application also provide a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is adapted to cause the computer to perform a method according to embodiments of this application.
The exemplary embodiments of this application also provide a computer program product comprising a computer program, wherein the computer program is adapted to cause a computer to perform the method according to an embodiment of this application when executed by a processor of the computer.
Referring to fig. 3, a block diagram of a structure of an electronic device 300, which may be a server or a client of the present application, which is an example of a hardware device that may be applied to aspects of the present application, will now be described. Electronic device is intended to represent various forms of digital electronic computer devices, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the applications described and/or claimed herein.
As shown in fig. 3, the electronic device 300 includes a computing unit 301 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)302 or a computer program loaded from a storage unit 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the device 300 can also be stored. The calculation unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
A number of components in the electronic device 300 are connected to the I/O interface 305, including: an input unit 306, an output unit 307, a storage unit 308, and a communication unit 309. The input unit 306 may be any type of device capable of inputting information to the electronic device 300, and the input unit 306 may receive input numeric or character information and generate key signal inputs related to user settings and/or function controls of the electronic device. Output unit 307 may be any type of device capable of presenting information and may include, but is not limited to, a display, speakers, a video/audio output terminal, a vibrator, and/or a printer. The storage unit 308 may include, but is not limited to, a magnetic disk, an optical disk. The communication unit 309 allows the electronic device 300 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunications networks, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers and/or chipsets, such as bluetooth devices, WiFi devices, WiMax devices, cellular communication devices, and/or the like.
The computing unit 301 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 301 performs the respective methods and processes described above. For example, in some embodiments, the method of determining governing objectives of a secondary conversion source may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 300 via the ROM 302 and/or the communication unit 309. In some embodiments, the computing unit 301 may be configured by any other suitable means (e.g., by means of firmware) to perform a method of determining a governing target of a secondary conversion source.
Program code for implementing the methods of the present application may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this application, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
Claims (10)
1. A method for determining a management and control target of a secondary transformation source is characterized by comprising the following steps:
obtaining a plurality of samples of first pollutants in the atmosphere, and determining the concentration of each pollution source corresponding to the first pollutants in the plurality of samples based on the plurality of samples and a positive definite matrix factorization (PMF) model;
determining a first proportion of each pollutant in a second class of pollutants in a comprehensive source according to the concentration of each pollution source corresponding to the first class of pollutants in the plurality of samples, wherein the comprehensive source comprises a primary source and a secondary conversion source;
determining a second proportion of each pollutant in the second class of pollutants in the primary source respectively based on the acquired emission list data;
and determining a control target of a secondary conversion source based on the first proportion and the second proportion.
2. The method of claim 1, wherein the first type of contaminant comprises PM 2.5 Components, ions, metals, and a labeling gas;
the second type of pollutant comprises PM 2.5 A component and a tag gas;
wherein the PM 2.5 The component comprising NO 3 - 、SO 4 2- 、NH 4 + 、Na + 、K + 、Mg 2+ 、Ca 2+ 、Cl - 、Al、Si、K、Ca;
The ions comprising NO 3 - 、SO 4 2- 、NH 4 + 、Na + 、K + 、Mg 2+ 、Ca 2+ One or more of Cl < - >;
the metal comprises one or more of Al, Si, K, Ca, Mn, Fe, Cu, Zn, As, Ba and Pb;
the marker gas comprises NO 2 、SO 2 And one or more of CO.
3. The method of claim 1, wherein determining a second fraction of each pollutant in the second class of pollutants in the primary source based on the obtained emissions manifest data comprises:
acquiring emission list data, wherein the emission list data comprises the emission amount of each pollutant in the second type of pollutants corresponding to each pollution source;
and respectively determining a second proportion of each pollutant in the second type of pollutants in the primary sources according to the emission amount of each pollutant in the second type of pollutants corresponding to each pollution source.
4. The method of claim 3, wherein determining the second percentage of each pollutant in the second class of pollutants in the primary source according to the emission amount of each pollutant in the second class of pollutants corresponding to each pollution source comprises:
determining the total emission of each pollutant in the second pollutants according to the emission of each pollutant in the second pollutants corresponding to each pollution source;
for each pollutant in the second type of pollutant, calculating a ratio of the emission to the total emission corresponding to said each pollutant source, and determining a second proportion in the primary sources.
5. The method according to claim 1, wherein determining a governing objective of a secondary conversion source based on the first and second proportions comprises:
for each pollutant in the second type of pollutant, respectively determining the difference value of the first proportion and the second proportion of each pollution source;
and determining a control target of the secondary conversion source according to the difference value.
6. The method according to claim 5, wherein the determining a regulatory objective of a secondary conversion source according to the difference comprises:
if the difference is larger than 0, comparing the difference with a first preset threshold, and if the difference is larger than or equal to the first preset threshold, determining the conversion of the pollution source corresponding to the difference to the pollutant corresponding to the difference as a control target of a secondary conversion source;
and if the difference is smaller than 0, comparing the difference with a second preset threshold, and if the difference is smaller than or equal to the second preset threshold, determining the emission of the pollutant corresponding to the difference from the pollutant corresponding to the pollution source corresponding to the difference as a control target of the primary conversion source.
7. The method according to claim 1, wherein determining a governing objective of a secondary conversion source based on the first and second proportions comprises:
for each pollutant in the second type of pollutants, comparing the first proportion and the second proportion of each pollution source, and if the first proportion of a certain pollution source is greater than the second proportion, determining the conversion of the pollutant by the pollution source as a control target of a secondary conversion source; if the first proportion of a certain pollution source is smaller than the second proportion, the emission of the pollutant by the pollution source is determined as a control target of a primary source.
8. An apparatus for determining a regulatory target of a secondary conversion source, the apparatus comprising:
the system comprises an acquisition module, a detection module and a processing module, wherein the acquisition module is used for acquiring a plurality of samples of first pollutants in the atmosphere and determining the concentration of each pollution source corresponding to the first pollutants in the plurality of samples based on the plurality of samples and a positive definite matrix factorization (PMF) model;
the first determining module is used for determining a first proportion of each pollutant in the second type of pollutants in a comprehensive source according to the concentration of each pollution source corresponding to the first type of pollutants in the plurality of samples, wherein the comprehensive source comprises a primary source and a secondary conversion source;
the second determining module is used for determining a second proportion of each pollutant in the second type of pollutants in the primary source respectively based on the acquired emission list data;
and the third determination module is used for determining a control target of the secondary conversion source based on the first proportion and the second proportion.
9. An electronic device, comprising:
a processor; and
a memory for storing a program, wherein the program is stored in the memory,
wherein the program comprises instructions which, when executed by the processor, cause the processor to carry out the method according to any one of claims 1-7.
10. A non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method of any one of claims 1-7.
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Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN117116381A (en) * | 2023-09-08 | 2023-11-24 | 重庆市生态环境科学研究院 | Method for comprehensively analyzing contribution of fine particulate matter source based on receptor and chemical transmission model |
Citations (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107402284A (en) * | 2017-07-13 | 2017-11-28 | 南开大学 | The polynary source resolution algorithm of atmosphere pollution based on Gas identification |
CN207016738U (en) * | 2017-03-29 | 2018-02-16 | 北京金泰瑞和工程科技有限公司 | Coal gas secondary conversion device and coal gas preparation system |
CN110057725A (en) * | 2019-05-14 | 2019-07-26 | 华北电力大学 | A kind of sulfate origin analysis method in Atmospheric particulates based on sulfur isotope |
CN111368401A (en) * | 2020-02-20 | 2020-07-03 | 南开大学 | Tracing method and device for pollution source and storage medium |
CN111739588A (en) * | 2020-06-19 | 2020-10-02 | 中科三清科技有限公司 | Method and device for analyzing atmospheric pollutant source, storage medium and terminal |
CN111899817A (en) * | 2020-08-04 | 2020-11-06 | 中科三清科技有限公司 | Pollutant source analysis method and device |
CN112711893A (en) * | 2020-12-25 | 2021-04-27 | 中科三清科技有限公司 | Method and device for calculating contribution of pollution source to PM2.5 and electronic equipment |
CN113393058A (en) * | 2021-07-14 | 2021-09-14 | 成都佳华物链云科技有限公司 | Pollutant management and control method, prediction management and control method, real-time management and control method and device |
CN113672873A (en) * | 2021-08-25 | 2021-11-19 | 中科三清科技有限公司 | Pollutant source analysis method and device, electronic equipment and storage medium |
CN114252463A (en) * | 2021-12-20 | 2022-03-29 | 北京大学深圳研究生院 | Urban atmospheric particulate source analysis method |
CN114424058A (en) * | 2019-09-23 | 2022-04-29 | 广州禾信仪器股份有限公司 | Tracing method for VOCs pollution |
-
2022
- 2022-05-24 CN CN202210569072.2A patent/CN114974452B/en active Active
Patent Citations (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN207016738U (en) * | 2017-03-29 | 2018-02-16 | 北京金泰瑞和工程科技有限公司 | Coal gas secondary conversion device and coal gas preparation system |
CN107402284A (en) * | 2017-07-13 | 2017-11-28 | 南开大学 | The polynary source resolution algorithm of atmosphere pollution based on Gas identification |
CN110057725A (en) * | 2019-05-14 | 2019-07-26 | 华北电力大学 | A kind of sulfate origin analysis method in Atmospheric particulates based on sulfur isotope |
CN114424058A (en) * | 2019-09-23 | 2022-04-29 | 广州禾信仪器股份有限公司 | Tracing method for VOCs pollution |
CN111368401A (en) * | 2020-02-20 | 2020-07-03 | 南开大学 | Tracing method and device for pollution source and storage medium |
CN111739588A (en) * | 2020-06-19 | 2020-10-02 | 中科三清科技有限公司 | Method and device for analyzing atmospheric pollutant source, storage medium and terminal |
CN111899817A (en) * | 2020-08-04 | 2020-11-06 | 中科三清科技有限公司 | Pollutant source analysis method and device |
CN112711893A (en) * | 2020-12-25 | 2021-04-27 | 中科三清科技有限公司 | Method and device for calculating contribution of pollution source to PM2.5 and electronic equipment |
CN113393058A (en) * | 2021-07-14 | 2021-09-14 | 成都佳华物链云科技有限公司 | Pollutant management and control method, prediction management and control method, real-time management and control method and device |
CN113672873A (en) * | 2021-08-25 | 2021-11-19 | 中科三清科技有限公司 | Pollutant source analysis method and device, electronic equipment and storage medium |
CN114252463A (en) * | 2021-12-20 | 2022-03-29 | 北京大学深圳研究生院 | Urban atmospheric particulate source analysis method |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN117116381A (en) * | 2023-09-08 | 2023-11-24 | 重庆市生态环境科学研究院 | Method for comprehensively analyzing contribution of fine particulate matter source based on receptor and chemical transmission model |
CN117116381B (en) * | 2023-09-08 | 2024-05-03 | 重庆市生态环境科学研究院 | Method for comprehensively analyzing contribution of fine particulate matter source based on receptor and chemical transmission model |
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